Literature DB >> 24702740

Finding the genetic determinants of adverse reactions to radiotherapy.

T Rattay1, C J Talbot2.   

Abstract

Individual variation in radiosensitivity is thought to be at least partly determined by genetic factors. The remaining difference between individuals is caused by comorbidities, variation in treatment, body habitus and stochastic factors. Evidence for the heritability of radiosensitivity comes from rare genetic disorders and from cell-based studies. To what extent common and rare genetic variants might explain the genetic component of radiosensitivity has not been fully elucidated. If the genetic variants accounting for this heritability were to be determined, they could be incorporated into any future predictive statistical model of adverse reactions to radiotherapy. With the evolution of DNA sequencing and bioinformatics, radiogenomics has emerged as a new research field with the aim of finding the genetic determinants of adverse reactions to radiotherapy. Similar to the investigation of other complex genetic disease traits, early studies in radiogenomics involved candidate gene association studies--many plagued by false associations caused by low sample sizes and problematic experimental design. More recently, some promising genetic associations (e.g. with tumour necrosis factor) have emerged from large multi-institutional cohorts with built-in replication. At the same time, several small- to medium-sized genome-wide association studies (GWAS) have been or are about to be published. These studies will probably lead to an increasing number of genetic polymorphisms that may predict adverse reactions to radiotherapy. The future of the field is to create large patient cohorts for multiple cancer types, to validate the genetic loci and build reliable predictive models. For example, the REQUITE project involves multiple groups in Europe and North America. For further discovery studies, larger GWAS will be necessary to include rare sequence variants through next generation sequencing. Ultimately, radiogenomics seeks to predict which cancer patients will show radiosensitivity or radioresistance, so oncologists and surgeons can alter treatment accordingly to lower adverse reactions or increase the efficacy of radiotherapy.
Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer; genetics; head and neck cancer; normal tissue toxicity; polymorphism; prostate cancer

Mesh:

Substances:

Year:  2014        PMID: 24702740     DOI: 10.1016/j.clon.2014.02.001

Source DB:  PubMed          Journal:  Clin Oncol (R Coll Radiol)        ISSN: 0936-6555            Impact factor:   4.126


  10 in total

1.  Beyond mean pharyngeal constrictor dose for beam path toxicity in non-target swallowing muscles: Dose-volume correlates of chronic radiation-associated dysphagia (RAD) after oropharyngeal intensity modulated radiotherapy.

Authors: 
Journal:  Radiother Oncol       Date:  2016-02-17       Impact factor: 6.280

2.  Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.

Authors:  Jung Hun Oh; Sarah Kerns; Harry Ostrer; Simon N Powell; Barry Rosenstein; Joseph O Deasy
Journal:  Sci Rep       Date:  2017-02-24       Impact factor: 4.379

3.  The Patient Perspective on Radiogenomics Testing for Breast Radiation Toxicity.

Authors:  T Rattay; R P Symonds; S Shokuhi; C J Talbot; J B Schnur
Journal:  Clin Oncol (R Coll Radiol)       Date:  2017-12-26       Impact factor: 4.126

4.  Research status and prospects of biomarkers for nasopharyngeal carcinoma in the era of high‑throughput omics (Review).

Authors:  Shan-Qiang Zhang; Su-Ming Pan; Si-Xian Liang; Yu-Shuai Han; Hai-Bin Chen; Ji-Cheng Li
Journal:  Int J Oncol       Date:  2021-03-02       Impact factor: 5.650

Review 5.  Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature.

Authors:  Xi Wang; Bin-Bin Li
Journal:  Front Genet       Date:  2021-02-10       Impact factor: 4.599

6.  Genetic Variability of Antioxidative Mechanisms and Cardiotoxicity after Adjuvant Radiotherapy in HER2-Positive Breast Cancer Patients.

Authors:  Tanja Marinko; Jakob Timotej Stojanov Konda; Vita Dolžan; Katja Goričar
Journal:  Dis Markers       Date:  2020-12-19       Impact factor: 3.434

Review 7.  Clinical and Functional Assays of Radiosensitivity and Radiation-Induced Second Cancer.

Authors:  Mohammad Habash; Luis C Bohorquez; Elizabeth Kyriakou; Tomas Kron; Olga A Martin; Benjamin J Blyth
Journal:  Cancers (Basel)       Date:  2017-10-27       Impact factor: 6.639

8.  A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials.

Authors:  Joshua S Niedzielski; Jinzhong Yang; Francesco Stingo; Zhongxing Liao; Daniel Gomez; Radhe Mohan; Mary Martel; Tina Briere; Laurence Court
Journal:  Sci Rep       Date:  2017-07-20       Impact factor: 4.379

9.  Predictive value of single nucleotide polymorphisms in XRCC1 for radiation-induced normal tissue toxicity.

Authors:  Jing Zhao; Zheng Zhi; Ming Zhang; Qingxia Li; Jing Li; Xiao Wang; Chunling Ma
Journal:  Onco Targets Ther       Date:  2018-07-06       Impact factor: 4.147

Review 10.  Superoxide Dismutase Administration: A Review of Proposed Human Uses.

Authors:  Arianna Carolina Rosa; Daniele Corsi; Niccolò Cavi; Natascia Bruni; Franco Dosio
Journal:  Molecules       Date:  2021-03-25       Impact factor: 4.411

  10 in total

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